Re-examination of phase relations between solid solutions in R4Al2O9-R4Si2N2O7-R4Si2O10 (R=Y,Gd, Yb) systems

Samples in Si–Al-R-O-N (R = Y, Gd, Yb) systems were prepared by solid-state reactions using R₂O₃, Al₂O₃, SiO₂ and Si₃N₄ powders as starting materials. X-ray diffraction was done to investigate RAM-J(R) solid solutions [RAM = R₄Al₂O₉, J(R) = R₄Si₂N₂O₇] formation and their equilibrium with RSO (R₄Si₂O₁₀). Phase relations between RAM, J(R) and RSO at 1700 °C were summarized in a phase diagram. It was determined that a limited solid solution of RAM and RSO could be formed along RAM-RSO tie-line, while RAM and J(R) form a continuous solid solution along RAM-J(R) tie-line. In RAM-J(R)-RSO ternary systems, the RAM-J(R) tie-lines were extended towards the RSO corner to form a continuous solid solution area of JRAMss (R = Y, Gd, Yb). The established phase relations in the Si–Al-R-O-N (R = Y, Gd, Yb) systems may facilitate compositional selections for developing JRAMss as monolithic ceramics or for SiC/Si₃N₄ based composites using the solid-solutions as a second refractory phase.     

Organic mesh template-based laminated object manufacturing to fabricate ceramics with regular micron scaled pore structures

A new aqueous slurry-based laminated object manufacturing process for porous ceramics is proposed: firstly, an organic mesh sheet is pre-paved as a pore-forming template before slurry layer scraping; secondly, the 2D pattern is built with laser outline cutting of the dried mesh–ceramic composite layer; finally, the pore structure is formed after degreasing and sintering. Alumina parts with porosities of 51.5 %, round hole diameters of 80 ± 5 μm were fabricated using 70 wt. % solid content slurry and 100 mesh nylon net. Using an organic mesh as the framework and template not only reduces the risk of damage of the green body but also ensures the regularity, uniformity and connectivity of the micron scaled pore network. The layer-by-layer drying method avoids the delamination phenomenon and improves the paving density. The new method can realize the flexible design of the pore structure by using various organic mesh templates.     

Targeted editing of intronic-splicing silencer enhancement of SMN2 Exon 7 inclusion by CRISPR/Case 9

Spinal muscular atrophy (SMA) is an autosomal recessive hereditary neuromuscular disease. Exon 7 and 8 of survival of motor neuron 1 (SMN1) gene or only exon 7 homology deletion leads to the failure to produce a full-length SMN gene. The copy number of SMN2 gene with high homology of SMN1 affects the degree of disease and was the target gene for targeting therapy, in which splicing silencer in intron 7 was the key to suppress the inclusion of exon 7. In this study, we projected to use CRISPR/Case 9 for the targeted editing of intronic-splicing silencer (ISS) sequence to promote the inclusion of SMN2 exon 7 and increase the production of SMN2 full-length (FL) gene expression. It happens that there was a protospacer adjacent motif (PAM) at one end of the ISS sequence according to the design of sgRNA. The recombinant vector of sgRNA HSMN2 CRISPR/Case 9 was constructed and transfected into HEK293 cells. Sequencing results showed that the ISS sequence could be edited accurately and targeting in the predicted direction, in which deleting small fragments, inserting small amounts and mutation. Quantitative analysis of RT-PCR products by restriction enzyme of DdeI digestion showed that the FL of SMN2 increased by 8% (P < 0.05). In the primary cultured chondrocytes of SMA mice, in which sgRNA HSMN2 CRISPR/Case9 recombinant vector transfection could increase the SMN2 FL gene by 23% (P < 0.05) and significantly improve SMN protein levels (P < 0.05). CRISPR/Case 9 is an effective tool for gene editing and therapy of hereditary diseases, but it is rarely reported in the treatment of SMA diseases. This study shows that CRISPR/Case 9 was first used for the precision target of ISS sequence editing, which can effectively promote the production of SMN2 FL gene expressions, in which there was an important clinical reference value.     

Exploration of GH94 Sequence Space for Enzyme Discovery Reveals a Novel Glucosylgalactose Phosphorylase Specificity

The substantial increase in DNA sequencing efforts has led to a rapid expansion of available sequences in glycoside hydrolase families. The ever-increasing sequence space presents considerable opportunities for the search for enzymes with novel functionalities. In this work, the sequence-function space of glycoside hydrolase family 94 (GH94) was explored in detail, using a combined approach of phylogenetic analysis and sequence similarity networks. The identification and experimental screening of unknown clusters led to the discovery of an enzyme from the soil bacterium Paenibacillus polymyxa that acts as a 4-O-β-d -glucosyl-d -galactose phosphorylase (GGalP), a specificity that has not been reported to date. Detailed characterization of GGalP revealed that its kinetic parameters were consistent with those of other known phosphorylases. Furthermore, the enzyme could be used for production of the rare disaccharides 4-O-β-d -glucosyl-d -galactose and 4-O-β-d -glucosyl-l -arabinose. Our current work highlights the power of rational sequence space exploration in the search for novel enzyme specificities, as well as the potential of phosphorylases for rare disaccharide synthesis.     

A comprehensive survey on computer vision based concepts,methodologies, analysis and applications for automatic gun/knife detection

The ability to detect gun and gun held in hand or other body parts is a typical human skill. The same problem presents an imperative task for computer vision system. Automatic observer independent detection of hand held gun or gun held in the other body part, whether it is visible or concealed, provides enhance security in vulnerable places and initiates appropriate action there. Compare to the automatic object detection systems, automatic detection of gun has very few successful attempts. In the present scope of this paper, we present an extensive survey on automatic detection of gun and define a taxonomy for this particular detection system. We also describe the inherent difficulties related with this problem. In this survey of published papers, we examine different approaches used in state-of-the-art attempts and compare performances of these approaches. Finally, this paper concludes pointing to the possible research gaps in related fields.     

Image sequence-based risk behavior detection of power operation inspection personnel

A novel image sequence-based risk behavior detection method to achieve high-precision risk behavior detection for power maintenance personnel is proposed in this paper. In this method, the original image sequence data is first separated from the foreground and background. Then, the free anchor frame detection method is used in the foreground image to detect the personnel and correct their direction. Finally, human posture nodes are extracted from each frame of the image sequence, which are then used to identify the abnormal behavior of the human. Simulation experiment results demonstrate that the proposed algorithm has significant advantages in terms of the accuracy of human posture node detection and risk behavior identification.     

Feasibility of high performance in p-type Ge1−xBixTe materials for thermoelectric modules

GeTe is a promising candidate for the fabrication of high-temperature segments for p-type thermoelectric (TE) legs. The main restriction for the widespread use of this material in TE devices is high carrier concentration (up to ∼ 10²¹ cm⁻³), which causes the low Seebeck coefficient and high electronic component of thermal conductivity. In this work, the band structure diagram and phase equilibria data have been effectively used to attune the carrier concentration and to obtain the high TE performance. The Ge_1−xBi_xTe (x = 0.04) material prepared by the Spark plasma sintering (SPS) technique demonstrates a high power factor accompanied by moderate thermal conductivity. As a result, a significantly higher dimensionless TE figure of merit ZT = 2.0 has been obtained at ∼ 800 K. Moreover, we are the first to propose that application of the developed Ge_1−xBi_xTe (x = 0.04) material in the TE unicouple should be accompanied by SnTe and CoGe₂ transition layers. Only such a unique solution for the TE unicouple makes it possible to prevent the negative effects of high contact resistance and chemical diffusion between the segments at high temperatures.     

Crystal structure,polarization properties and reverse nonlinearity of solid solutions of the KNN-PZT system in a wide range of external influences

Experimental research of the crystal structure, polarization properties, and reverse nonlinearity of ceramic solid solutions of the (1-x) (Na_0·5K_0.5)NbO₃-xPb(Ti_0·5Zr_0.5)O₃ (KNN-PZT) quasi-binary system with 0.0 = x ≤ 1.0 in a wide range of external influences (temperatures, strength of dc/ac fields) has been done. Based on the X-ray structural data, an x-T diagram of the system has been constructed, and correlations of the behavior of the macroproperties of solid solutions with the features of their phase states with the temperature change have been established. It has been concluded that it is advisable to use the proposed compositions when designing microelectronic devices operating in various extreme conditions.     

YOLSO: You Only Look Small Object

Small object detection is challenging and far from satisfactory. Most general object detectors suffer from two critical issues with small objects: (1) Feature extractor based on classification network cannot express the characteristics of small objects reasonably due to insufficient appearance information of targets and a large amount of background interference around them. (2) The detector requires a much higher location accuracy for small objects than for general objects. This paper proposes an effective and efficient small object detector YOLSO to address the above problems. For feature representation, we analyze the drawbacks in previous backbones and present a Half-Space Shortcut(HSSC) module to build a background-aware backbone. Furthermore, a coarse-to-fine Feature Pyramid Enhancement(FPE) module is introduced for layer-wise aggregation at a granular level to enhance the semantic discriminability. For loss function, we propose an exponential L1 loss to promote the convergence of regression, and a focal IOU loss to focus on prime samples with high classification confidence and high IOU. Both of them significantly improves the location accuracy of small objects. The proposed YOLSO sets state-of-the-art results on two typical small object datasets, MOCOD and VeDAI, at a speed of over 200 FPS. In the meantime, it also outperforms the baseline YOLOv3 by a wide margin on the common COCO dataset.